使用Mumford-Shah / Total变化正则化对民用结构检查的无人机航拍图像去模糊

A. Hammer, J. Dumoulin, B. Vozel, K. Chehdi
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引用次数: 5

摘要

本文在实际应用的背景下解决了盲图像反卷积的问题。我们研究的目的是提出一种新开发的技术,并测试其对用于桥梁土木检查的无人机(无人机)获取的图像的去模糊能力。我们提出了一种基于双重正则化原则的方法,正如You和Kaveh所介绍的那样。我们的方案是在模糊核上使用总变差(TV)正则化项,在图像上使用基于Mumford-Shah函数的正则化项。我们给出了最小化算法的细节,并在合成图像和真实图像上提供了一些初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deblurring of UAV aerial images for civil structures inspections using Mumford-Shah / Total variation regularisation
This paper addresses the problem of blind image deconvolution, in the context of a real-life application. The purpose of our study is to present a newly developed technique, and to test its deblurring capabilities on images acquired by an UAV (unmanned aerial vehicle) used for the civil inspection of bridges. We propose an approach based on the double regularisation principle, as introduced by You and Kaveh. Our scheme lies on the use of a total variation (TV) regularisation term on the blur kernel, and a Mumford-Shah functional based one, on the image. We give the details of the minimisation algorithm and provide some preliminary results both on synthetical and real images.
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